Internet-scale pattern recognition: new techniques for voluminous data sets and data clouds

"This cutting-edge reference outlines the underlying theory and principles of efficient and effective distributed pattern recognition involving one-shot learning and in-network processing for different types of applications, including multimedia retrieval systems and event detection over differ...

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Bibliographische Detailangaben
Beteilige Person: Muhamad Amin, Anang Hudaya (VerfasserIn)
Weitere beteiligte Personen: Khan, Asad (MitwirkendeR), Nasution, Benny (MitwirkendeR)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: 2013
Schlagwörter:
Links:https://learning.oreilly.com/library/view/-/9781466510975/?ar
Zusammenfassung:"This cutting-edge reference outlines the underlying theory and principles of efficient and effective distributed pattern recognition involving one-shot learning and in-network processing for different types of applications, including multimedia retrieval systems and event detection over different network environments. Investigating one-shot learning and in-network processing as complementary mechanisms for efficient and accurate distributed pattern analyses, it presents the technical aspects related to the development of scalable pattern recognition using a number of contemporary application development tools. It also considers scalability of pattern recognition schemes when dealing with such data"--
Beschreibung:Includes bibliographical references and index. - Print version record
Umfang:1 Online-Ressource (xviii, 179 Seiten) illustrations
ISBN:1466510978
9781466510975